The Value of Multidimensional Modeling with Quantrix – An Interview with Software Executive George Pappas

Many people purchase Quantrix because they are looking for a tool that can delve more deeply into their data than typical spreadsheet solutions. One of the important capabilities that Quantrix delivers is its ability to model complex information relationships in multiple dimensions. At Quantrix’s 2014 Seminar by the Sea, VC-affiliated Software Executive, George Pappas shared how he uses Quantrix to provide in-depth analytical insight to help high-growth companies succeed. Following is a discussion with him about his use of Quantrix.

Why do you use Quantrix?

I work with venture-capital-backed companies to help them get to the next stage of their evolution. As a member of The Edison Venture Partners Director’s Network, I have observed similar patterns of complexity challenges across their portfolio companies. The need to analyze activities and behaviors that drive financial results requires more modeling power than the spreadsheet metaphor. Quantrix is a superior tool for modeling that lets me do things that are too rudimentary in Excel.

You work with software companies that either use or want to migrate to a software-as-a-service model. What challenges does that bring?

Rather than getting licensing revenues up front, companies get a monthly subscription fee. It’s a very challenging business model if you have a complex product. The cost of building and implementing a SaaS customer is complex, so you have the same cost as for a customer purchasing a license, but much less up-front revenue and cash, so you have to be careful.

What are some of the other common concerns of start-up companies?

When you try to grow fast, the risk goes up. And the team has to grow from doing things themselves to managing things, and that brings a lot of complexity. There are so many challenges, really, and people tend to make emotional rather than objective decisions. They also tend to make their models match their expectations. But really, the levers that drive results are too complicated in most cases to model in a program like Excel. People end up simplifying their assumptions and inputs to their model to drive what they expect will be the financial results, such as, it will take us one month to get five new customers. This happens not just because the finance person might not understand the detailed sales process and key drivers, but also because they are not comfortable in using Excel to model the assumptions that drive the results.

So, tools can be a barrier to insight?

The problem is not modeling financials; it’s modeling the activities that drive the financial result in a way that is rich enough to test your assumptions. I spend a lot of time working with the CFOs at companies, and asking them about their financial and operating models. How much expense does it really take to implement a customer? How long does it take? What resources do we need, and how much do they cost? You need a modeling tool that can describe in a rich way the activities that you need to drive the outcomes that you want and validate the model by seeing the results in multiple perspectives simultaneously; that is where Quantrix’s multi-dimensionality is so valuable. Excel offers a flat, two-dimensional perspective with simplified assumptions. But you can get something much richer and more adaptable with Quantrix.

Give us an example.

Ok, one of my companies developed assumptions for new customer growth including the sales cycle, close rate, deployment time, and economics.

The next step was to dig into that, and find out what it meant. Take a look at the next figure – this is a flattened Excel view of the sales booking of these new customers, and the assumptions seem reasonable.

But then you look at the next figure. This is a multidimensional Quantrix model that shows the reality: if you sell this way, and your deployment time is as predicted, then you have to be prepared to handle rolling out 70 locations in one month at peak load and staffing.

That’s the difference between two-dimensional Excel models and multidimensional Quantrix models – you get information you need to do something meaningful, or make a different choice. These are things that most people understand intuitively, but seeing the cascading effects of modeling assumptions is invaluable.

What often happens with planning is that your assumptions seem right, but when you add them up together, you see that something is not working. By modeling more richly, you can see what will really happen after calculating in all of the dependencies. With Quantrix, you can see the problems clearly before they happen. That’s a big-time selling point over Excel.

How did your client react to that information?

We changed the professional services staffing, and we adjusted compensation sales goals. We did some rethinking on our sales strategy and plans. By using Quantrix, we were able to see the impact of certain assumptions, and get a real picture of our risk. It’s all about risk and execution, and being able to model more richly in Quantrix, we were able to adjust.

Where should new Quantrix users start when they begin to model?

Given the things that Quantrix does well – multidimensional analysis, and ripping things apart and calculating on baseline data – people should try to really understand what’s going on with their customers, activities and the revenue they generate. That’s something most companies have a poor understanding of. Every business cares about revenue, so this is a good place to start with Quantrix.